YHTTAY-24487 Introduction to High-Throughput Data Analysis, 5 cr
Additional information
Opintojakson oikea koodi on BTK6002 Introduction to High-Throughput Data Analysis
Täydelliset tiedot löytyvät opiskelijan oppaasta https://www.tuni.fi/opiskelijanopas/opintotiedot/
Ilmoittautuminen opintojaksolle vain NettiOpsun kautta. POPin kautta tehtyjä ilmoittautumisia ei huomioida.
The course is only intended for degree students
Person responsible
Outi Väisänen
Learning Outcomes
After the course, the student can: - compare sequencing and microarray technologies used in high-throughput analysis and choose suitable ones for the analysis required. - explain the principles of measurement technologies covered and how various inherent errors and biases of the measurement techniques affect the analysis. - apply common methods and algorithms to extract information from microarray and sequencing measurements. - discuss the statistical principles underlying the data analysis methods above and identify the benefits and weaknesses of each method. - select suitable algorithms for the analysis and justify the choice. - build data analysis pipelines for microarray and sequencing data analysis.
Content
| Content | Core content | Complementary knowledge | Specialist knowledge |
| 1. | Deep sequencing technologies DNA microarrays Statistical methods for the analysis of high-throughput measurement data Data classification and clustering |
Correspondence of content
| Course | Corresponds course | Description |
| YHTTAY-24487 Introduction to High-Throughput Data Analysis, 5 cr | YHTTAY-24486 High-throughput Data Analysis, 5 cr |